This paper reviews the practice and performance of revenue forecasting in selected OECD countries. While the mean forecast errors are small in most countries, the precision of the forecasts measured by the standard deviation of the forecast error differs substantially across countries. Based on...

In this paper, we disentangle tax revenue forecast errors into influences stemming from wrong macroeconomic assumptions and false predictions of the elasticities linking the tax base to its corresponding tax type. Across six tax types and the overall tax sum for Germany, we find a heterogeneous...

We forecast New York state tax revenues with a mixed-frequency model using a number of machine learning techniques. We found boosting with two dynamic factors extracted from a select list of New York and U.S. leading indicators did best in terms of correctly updating revenues for the fiscal year...

This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a...

This paper provides a general strategy for analyzing monetary policy in real time which accounts for data uncertainty without explicitly modelling the revision process. The strategy makes use of all the data available from a real-time data matrix and averages model estimates across all data...

Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore several new forecasting...

We examine the quantitative predictions of heterogeneous firm models à la Melitz (2003) in the context of the Canada - US Free Trade Agreement (CUSFTA) of 1989. We compute predicted increases in trade flows and measured productivity across a range of standard models and compare them to the...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

Previous assessments of nominal exchange rate determination have focused upon a narrow set of models typically of the 1970 s vintage, including monetary and portfolio balance models. In this paper we re-assess the in-sample fit and out-of-sample prediction of a wider set of models that have been...